To establish the optimal environmental control in hydroponics, we measured the diurnal courses of net CO
2 uptake and NO
3- consumption of tomato plant cultivated in nutrient film culture and then tried to make the dynamic models of these physiological processes as affected by light intensity based on system identification. Furthermore, online identification was applied to these processes.
Two types of dynamic models which are the linear model obtained by the method of least squares and the nonlinear model obtained by the GMDH (Group Method of Data Handling) were used in the identification.
Using the nonlinear model, we could identify the processes of net CO
2 uptake and NO
3- consumption as affected by light intensity with satisfactory results. On the other hand, using the linear model in the process of NO
3- consumption to light intensity increased the mean square error between the calculated and the observed responses. In the process of net CO
2 uptake to light intensity, however, we could identify using the linear model with satisfactory results. This implies that online identification based on a linear model is effective to the process of net CO
2 uptake as affected by the light intensity from the view of efficient identification.
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